According to David Schubmehl, research director, Cognitive Systems and Content Analytics at IDC, “Software developers and end user organizations have already begun the process of embedding and deploying cognitive/artificial intelligence into almost every kind of enterprise application or process”

“Recent announcements by several large technology vendors and the booming venture capital market for AI startups illustrate the need for organizations to be planning and undertaking strategies that incorporate these wide-ranging technologies,” he said.

Schubmehl said identifying, understanding, and acting on the use cases, technologies, and growth opportunities for cognitive/AI systems will be a differentiating factor for most enterprises and the digital disruption caused by these technologies will be significant.

The ability to recognize and respond to data flows using algorithms and rule-based logic enables cognitive/AI systems to automate a broad range of functions across many industries.

The use cases that are attracting the most investment in 2016 are automated customer service agents, quality management investigation and recommendation systems, diagnosis and treatment systems, and fraud analysis and investigation.

The use cases that will experience the fastest revenue growth over the next five years are public safety and emergency response, pharmaceutical research and discovery, diagnosis and treatment systems, supply and logistics, quality management investigation and recommendation systems, and fleet management.

“In these segments, we find a wealth of unstructured data, a desire to harness insights from this information, and an openness to innovative technologies. Furthermore, the value proposition of cognitive systems aligns well with industry executives’ chief priorities.”

For instance, Goepfert said, cognitive technologies are being used in the banking industry to detect and combat fraud, which is a top industry pain point.

In manufacturing, executives cite improving product is a top initiative. In this case, cognitive systems recognize and know how to respond to dynamic fluctuations in product specs by adapting the production to stay within quality targets.

The industries that will invest the most in cognitive/AI systems in 2016 are banking and retail, followed by healthcare and discrete manufacturing.

Combined, these four industries will generate more than half of all worldwide cognitive/AI revenues in 2016, with banking and retail each delivering nearly $1.5 billion.

Healthcare and discrete manufacturing will deliver the greatest revenue growth over the 2016-2020 forecast period, with CAGRs of 69.3 per cent and 61.4 per cent, respectively. Education and process manufacturing will also experience significant growth over the forecast period.

It also includes cognitive software platforms, which facilitate the development of intelligent, advisory, and cognitively enabled solutions.

As both the largest and fastest-growing category, cognitive applications spending is forecast to reach $18.2 billion in 2020.

Cognitive/AI-related services (business services and IT consulting) represent the second largest revenue category while hardware revenues (primarily from dedicated purchases of servers and storage) will grow nearly as fast as software with five-year CAGRs of more than 60 per cent.

On a geographic basis, North America (the United States and Canada) is by far the largest region for cognitive/AI spending with 2016 revenues approaching $6.2 billion.

Europe, the Middle East and Africa (EMEA) will remain the second largest region throughout the forecast, but cognitive/AI revenues from Asia/Pacific including Japan will nearly close the gap with EMEA by 2020.

The spending guide quantifies the cognitive computing opportunity by providing data for more than 20 use cases across 19 industries in eight regions. Data is also available for the related hardware, software, and services categories.

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Unlike any other research in the industry, the detailed segmentation and timely, global data is designed to help suppliers targeting the market to identify market opportunities and execute an effective strategy.

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